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for this position has a BSc and MSc in environmental sciences, physical geography or biology, knowledge of metagenomic analyses, and a passion for the natural environment. This fully funded studentship is part of
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. Despite all the positive impacts that automation systems can bring, the industry yet needs these advancements to provide value for the business, contribute to economic growth, and assist the industry
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, these systems serve as complex functional approximators trained over an input-output data set. ‘Second Wave AI’ is the term used to describe the current glut of 'machine learning' style intelligence, where
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to combine the two and achieve property enhancement and advanced functionality within the same material solution. This project is inspired by these developments to put forward a solution that will endow
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Applications are invited for doctoral level research into sustainable manufacturing operations and management. More specifically, the candidate will undertake research activities into eco-design
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sponsor (local government or industry) will need to provide their own financial support in relation to tuition fees, research support fees and living expenses. Cranfield Doctoral Network Research students
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. This is a self funded PhD opportunity. Find out more about tuition fees. Cranfield Doctoral Network Research students at Cranfield benefit from being part of a dynamic, focused and professional study
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sponsor Cranfield Doctoral Network Research students at Cranfield benefit from being part of a dynamic, focused and professional study environment and all become valued members of the Cranfield Doctoral
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This studentship is restricted to British, USA or Australian nationals. Cranfield Doctoral Network Research students at Cranfield benefit from being part of a dynamic, focused and professional study environment and
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interoperability to be in place to sustain the potential value that we can get from Cyber Physical Systems (CPSs) and the ever-growing richness of information. Interoperability is a vital aspect of modern technology